METHOD, SYSTEM, AND APPARATUS FOR DETERMINING A PREDICTED RATING

• US 20100088265A1
• Filed: 10/05/2009
• Published: 04/08/2010
• Est. Priority Date: 10/03/2008
• Status: Active Grant

• Current Assignee: Sift LLC
• Original Assignee: Sift LLC
• Inventors: Pohl, Daniel
• Granted Patent: US 8,732,104 B2
• Time in Patent Office: Days
• US Class Current: 706/46
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Embodiments of the invention can incorporate a method and interface to accomplish one or more of the following three processes: input, analysis, and output. With respect to input, the user(s) identifier(s), item(s) identifier(s), and user(s)-item(s) rating data 22 can be accepted through an interface 23 from an application 21. With respect to analysis, the method and interface can then take the actual user-item ratings 31 and process 32 the data to generate and store item predictor information 33. The predicted user-item ratings 41 and the actual user-item ratings 42 can then be outputted by, for example, passing these outputs to the application via an interface 44.

Claims

1. A method of determining a predicted rating, comprising:

receiving a plurality of data sets, wherein each data set comprises a user identifier, an item identifier, and a rating, wherein for each data set each user identifier identifies a user of a plurality of users, each item identifier identifies an item of a plurality of items, and each rating is a rating by the user identified by the user identifier in the data set of the item identified by the item identifier in the data set;

identifying, via a suitably programmed computer, a pair of items the ratings of which for any user can be used to predict a rating for the other item in the pair of items for the same user, based on an analysis of ratings for the pair of items; and

determining a predicted rating for a given item of the identified pair of items for a given user based on a given rating of the other item of the pair of items for the given user.

2. The method according to claim 1, wherein identifying the pair of items comprises identifying a pair of items having ratings that are highly correlated.

3. The method according to claim 2, wherein identifying the pair of items having ratings that are highly correlated comprises calculating a statistical variance of a set of ratings, wherein the set of ratings include ratings of the items in the pair of items.

4. The method according to claim 3, wherein the set of ratings includes all ratings in the plurality of data sets of the items in the pair of items.

5. The method according to claim 3, wherein the set of ratings includes only ratings from users having ratings for both items in the pair of items.

6. The method according to claim 3, wherein identifying the pair of items having ratings that are highly correlated comprises finding that the statistical variance of the set of ratings is less than a threshold value.

7. The method according to claim 3, wherein identifying the pair of items having ratings that are highly correlated comprises finding that the statistical variance of the set of ratings is less than a statistical variance of a second set of ratings including of ratings of items from other pair of items.

8. The method according to claim 3, wherein calculating the statistical variance of the set of ratings comprises using a statistical method selected from the group consisting of standard deviation, Horting, Pearson, Pearson product-moment correlation coefficient, Pearson R, Pearson T, Spearman'"'"'s rank correlation coefficient, Kendall'"'"'s tau rank correlation coefficient, Confounding variable, and Point-Biserial Correlation.

9. One or more computer-readable media having computer-useable instructions embodied thereon for performing a method of determining a predicted rating, the method comprising:

receiving a plurality of data sets, wherein each data set comprises a user identifier, an item identifier, and a rating, wherein for each data set each user identifier identifies one of a plurality of users, each item identifier identifies one of a plurality of items, and each rating is a rating by the user identified by the user identifier in the data set of the item identified by the item identifier in the data set;

identifying a pair of items, each of the ratings of which for any user can be used to predict a rating for the other item in the pair of items for the same user, based on an analysis of ratings for the items in the pair of items; and

determining a predicted rating for a given item of the identified pair of items for a given user based on a given rating of the other item of the pair of items for the given user.

10. The media according to claim 9, wherein identifying the pair of items comprises identifying a pair of items having ratings that are highly correlated.

11. The media according to claim 10, wherein identifying the pair of items having ratings that are highly correlated comprises calculating a statistical variance of a set of ratings, wherein the set of ratings include ratings of the items in the pair of items.

12. The media according to claim 11, wherein the set of ratings includes all ratings in the plurality of data sets of the items in the pair of items.

13. The media according to claim 11, wherein the set of ratings includes only ratings from users having ratings for both items in the pair of items.

14. The media according to claim 11, wherein identifying the pair of items having ratings that are highly correlated comprises finding that the statistical variance of the set of ratings is less than a threshold value.

15. The media according to claim 11, wherein identifying the pair of items having ratings that are highly correlated comprises finding that the statistical variance of the set of ratings is less than a statistical variance of a second set of ratings including of ratings of items from other pair of items.

16. The media according to claim 11, wherein calculating the statistical variance of the set of ratings comprises using a statistical method selected from the group consisting of standard deviation, Horting, Pearson, Pearson product-moment correlation coefficient, Pearson R, Pearson T, Spearman'"'"'s rank correlation coefficient, Kendall'"'"'s tau rank correlation coefficient, Confounding variable, and Point-Biserial Correlation.

17. A system for providing a predicted rating, comprising:

an input interface, wherein the input interface is adapted to receive a plurality of data sets, wherein each data set comprises a user identifier, an item identifier, and a rating, wherein for each data set each user identifier identifies one of a plurality of users, each item identifier identifies one of a plurality of items, and each rating is a rating by the user identified by the user identifier in the data set of the item identified by the item identifier in the data set;

a predictive pair identification module, wherein the predictive pair identification module identifies a pair of items, each of the ratings of which for any user can be used to predict a rating for the other item in the pair of items for the same user, based on an analysis of ratings for the items in the pair of items;

a predictive rating determination module, wherein the predictive rating determination module determines a predicted rating for a given item of the identified pair of items for a given user based on a given rating of the other item of the pair of items for the given user; and

an output interface, wherein the output interface presents the predicted rating.

18. The system according to claim 17, further comprising:

one or more computer readable media having computer-useable instructions embodied thereon for performing the functions of the predictive pair identification module and the predictive rating determination module;

one or more processors for executing the computer-useable instructions on the one or more computer readable media; and

a memory for storing one or more of the following;

some or all of the plurality of data sets;

the pair of items the ratings of which for a user can be used to predict a rating for the other item in the pair of items for the user; and

the predicted rating.

19. The system according to claim 18, further comprising an output device, wherein the output interface presents the predicted rating via the output device.

20. The system according to claim 19, wherein the output device comprises a computer monitor.

21. The system according to claim 19, wherein the output device comprises a communication device that communicates the predicted rating to another computer system.

22. The system according to claim 21, wherein the output device comprises a modem that communicates the predicted rating to a computer via a network.

23. An article of manufacture, comprising:

one or more computer-readable media having computer-useable instructions embodied thereon for providing an interface from a computer program that provides access to a set of user ratings to a computer program that determines a predicted rating based on the set of user ratings, said interface consisting essentially of;

a first input field, wherein the first input field receives a user identifier, wherein the user identifier identifies one of a plurality of users;

a second input field, wherein the second input field receives an item identifier, wherein the item identifier identifies one of a plurality of items; and

a third input field, wherein the third input field receives an item rating, wherein the item rating is a rating by the user identified by the user identifier of the item identified by the item identifier.